1. Field of the Invention
The present invention relates to automated factories and, in particular, to a system and method for flexible, operatorless manufacturing.
2. Discussion of the Prior Art
Conventional industrial material handling systems can be divided into three general categories: processing by class, processing by real time material control and processing by synchronous material movements.
Systems that utilize processing by class include all serial process lines as well as some hardware-specific installations that allow for parallel process cells.
Serial systems, as the name implies, process material by passing it from one process cell to the next cell in a preconfigured line with no choice of which machine will perform the next process step. Serial process systems suffer from the limitation that the down time of the entire line is the compound of the down times of each of the individual process cells. If any process cell in a serial line is not functioning, then the entire line is not functioning. Although significant improvements can be made in serial systems by holding or buffering work in progress (WIP) between process steps to pad the effect of one cell's down time on other process steps, this buffered WIP not only increases the throughput time of the line, but also increases the overhead cost of WIP in the factory.
The most obvious shortcoming of a serial processing system is the requirement that each cell in the line process material at the same speed. Few production process lines utilize steps that each take the same amount of time. This means that fast process cells must remain idle while slow process cells complete their tasks. The net effect is that all cells in the system are governed by the slowest cell.
Serial manufacturing systems are analogous to daisy chain communications networks. A daisy chain network only works when all members of the chain are intact. Buffers can be used to minimize the impact of sporadically operating members, but buffers tend to slow down network throughput. Relationships between members must be static and simple. Furthermore, daisy chain network members can relate only to directly adjacent members on the network.
Examples of simple, well-known automated serial process lines include car washes and automatic film development machines.
In a modification of the standard serial process system, parallel cells are arranged in banks to perform each process step. The use of banks of cells makes it possible to use a different number of machines for different process steps. Process step cell banks can be sized so that the production rate of each process step is the same as that of the production rate of every other process step in the process line. This is called line balancing. Line balancing improves machine effectiveness compared to a pure serial line in applications that require different amounts of time to perform each process step.
For example, assume that a manufacturing line requires two process steps. The process cell for step 1 builds three parts per hour. The process cell for step 2 builds four parts per hour. Twenty-four parts per hour are desired. In a serial process line, eight discrete flow lines would be used, each composed of one process cell 1 and one process cell 2. The combined output of the eight flows would be twenty-four parts per hour. Each machine would be forced to run at three parts per hour, leaving process cell 2 idle in each flow 25% of the time.
Now assume that banks of process cells are used to perform the above-described process. The definition of a bank is "a number of process cells each of which performs an identical process". Material process status is monitored by marking the material carrier; in this case, the material carrier would be marked "not processed", "through process step one", or "finished"). The status of a carrier in a sequential manufacturing line can be inferred from the location of the carrier in the factory. A balanced pair of process banks can be constructed composed of eight cells of process step 1 for process bank 1 and six cells of process step 2 for process bank 2. Process bank 1 will output twenty-four parts per hour of half processed parts, and process bank 2 will complete these twenty-four units at the same rate. Therefore, no machines will be idle.
The use of banks of process cells also minimizes the effect of machine failure. If one of the machines performing each process step fails, the output of the serial line will drop by 2/8 of its capacity (assuming the failed machines were in different flows); in comparison, the output of the line using process banks will drop by only 1/8 of its capacity.
Another approach to serial processing is to use loops to feed parallel process cells. Material status is determined by identifying the loop or branch in the system in which the material carrier is located, or by the position of material status indicators built into the material carriers. The material status indicators can be mechanical buttons which typically record status as "processed" or "not processed", and, in some cases, "good" or "reject" material. Separate material carrier identification indicators can be used to uniquely identify each carrier.
Serial processing with parallel cells is analogous to a point-to-point network. The path a message may take in a point-to-point network must be established in advance at the time of system definition. Once the system has been defined, system redefinition is impractical because it takes too much time to change the network linkages to accommodate changes in data flow requirements.
A simple example of a serial process with parallel cells is a laundromat with one washing machine and more than one dryer.
As stated above, processing by class is best suited for production applications in which process cell linkages are simple and static. All of the information required for a routing decision to be made along the material path in a "processing by class" system is encoded in the material carrier signature. Material status is implied by the position of the material carrier in the system. Routing information does not change for a given carrier signature once the carrier is placed in the process line. The degree of expected control in a "processing by class" system does not require finer detail than the class of a carrier. Material need not be traced through the process line with any more specificity than the fact that the previous process step has been performed.
A second category of industrial material handling systems is processing by real time control. Real time control systems typically use a single host computer, which implies a potential single point of failure. Some real time systems use a back-up host, but these systems typically use a shared multi-drop communication media that can also be a single point of failure. Thus, in real time control systems, when the host computer stops or when host communication stops, so does production.
Real time control is best suited for production applications in which there is no requirement that processing continue while the host computer is off line. Factory size and complexity must be limited within the bounds of available computing power.
An example of a real time control system is a space craft launch, navigation, and fuel management system.
A third category of industrial material handling system is synchronous movement material handling. These systems typically use one or more queues which are waiting for a shared resource. In one such system, a resource detection conveyor system, material carriers returning to the main conveyor line are held until the returning carrier can be inserted into a gap in the main line traffic flow. Problems arise when loop traffic becomes too heavy and the main line becomes saturated with material waiting to be processed. In this instance, the main line acts like a bus-master forced to hold the token forever. Machines returning a material carrier to the main line in order to accept another carrier find it impossible to do so until the WIP levels are reduced. This scenario results in a stand off between the material handling system and the process machine. Both the material handling system and the machine require the other to initiate an action to reduce WIP on the main line.
Resource detection is analogous to token passing in networking architectures. Every network member must wait while a pre-requisite task is completed.
Examples of systems that use resource detection include airport traffic control queues for take-off and landing and toll road collection booths.
Resource detection works well when average demand for a resource is significantly below the peak demand for the same resource. Queues tend to average out demand and to decrease the instantaneous requirements, allowing average demand to decrease over time.
Dedicated resource systems, as the name implies, are limited in their ability to effectively use the resource. A resource that could do the job might be much more available, but is not dedicated to the required job. A simple analogy is the use of a private elevator as compared to an escalator; an escalator can handle much more traffic than a large number of private elevators.
Time slicing networks use a type of dedicated resource. Systems requiring the resource must wait for it while other systems that may not require use of the resource take a turn.
None of the systems described above provide all of the following desirable features in a single material handling system:
1. The capability to allow material to change carriers; PA1 2. The capability for dynamic re-routing; PA1 3. The capability to identify and re-dispatch lost material carriers; PA1 4. The capability to identify when and where the contents of a specific material carrier were processed for each step in the system, after the material is completely processed; PA1 5. The capability to orient, identify and verify material carriers; PA1 6. The capability to dynamically re-orient material carriers; and PA1 7. The capability to locate a specific material carrier within the material handling system within a specific time after issuing a location request.